Combine multiple sources to
increase the accuracy of data
Bridge the gaps in AI fusion by using reliable, tested human intelligence combined with automated scaling.
Combine multiple datasets
Solve the issues and discrepencies in combining datasets at scale
Align different sources
Gain a deeper understanding by analysing in multiple ways
Gain a new perspective
Discover new insights by looking from many different angles
Solve complex problems
Enable unique analysis techniques to tackle the hardest questions
Data fusion provides
new ways to look at data
Being able to combine multiple datasets makes for better decisions, especially when they are from entirely different sources. As well as cross checking results, it provides a new perspective to gain fresh insights and allows for a greater level of detail.
However, combining data sources comes with inherent friction, they often don’t line up correctly and decisions have to be made. We use human judgement to bridge the gap when aligning datasets and then automate this understanding to scale your fusion efforts.
all your data types
Detect objects and add context to analyse imagery
Detect and categorise shapes and patterns in imagery
Categorise, label and annotate video in real time
Boundary & route analysis
Understand and map out boundaries and routes
Scale your labelling with no compromise on quality
A core challenge of data labelling is scaling your team. While small pools of workers can’t handle large datasets and increase the risk of individual error, large pools are hard to manage and likely to be less focused or knowledgable.
We have a ten year track record of using existing pools to take the weight of crowd management off your shoulders of world class companies. Participant input is statistically weighted based on their track record to combining the results of many workers for any given task and ensure the highest quality results.
Focus on unique problems with high level configuration
We provide well-tested solutions that can be rapidly implemented for more straight forward tasks, helping you focus on the more important and high impact work.
For more difficult tasks, unknown problems or new areas of research, our flexible internal toolkit and extensive experience in crowd labelling allows us to design and deploy workflows which focus crowd effort onto your specific problem. No more generic ‘place a bounding box’ results.